Currently, in developed countries, nights are excessively illuminated (light at night), whereas daytime is mainly spent indoors, and thus people are exposed to much lower light intensities than under natural conditions. In spite of the positive impact of artificial light, we pay a price for the easy access to light during the night: disorganization of our circadian system or chronodisruption (CD), including perturbations in melatonin rhythm. Epidemiological studies show that CD is associated with an increased incidence of diabetes, obesity, heart disease, cognitive and affective impairment, premature aging and some types of cancer. Knowledge of retinal photoreceptors and the discovery of melanopsin in some ganglion cells demonstrate that light intensity, timing and spectrum must be considered to keep the biological clock properly entrained. Importantly, not all wavelengths of light are equally chronodisrupting. Blue light, which is particularly beneficial during the daytime, seems to be more disruptive at night, and induces the strongest melatonin inhibition. Nocturnal blue light exposure is currently increasing, due to the proliferation of energy-efficient lighting (LEDs) and electronic devices. Thus, the development of lighting systems that preserve the melatonin rhythm could reduce the health risks induced by chronodisruption. This review addresses the state of the art regarding the crosstalk between light and the circadian system.

The increased prevalence of circadian disruptions due to abnormal coupling between internal and external time makes the detection of circadian phase in humans by ambulatory recordings a compelling need. Here, we propose an accurate practical procedure to estimate circadian phase with the least possible burden for the subject, that is, without the restraints of a constant routine protocol or laboratory techniques such as melatonin quantification, both of which are standard procedures. In this validation study, subjects (N = 13) wore ambulatory monitoring devices, kept daily sleep diaries and went about their daily routine for 10 days. The devices measured skin temperature at wrist level (WT), motor activity and body position on the arm, and light exposure by means of a sensor placed on the chest. Dim light melatonin onset (DLMO) was used to compare and evaluate the accuracy of the ambulatory variables in assessing circadian phase. An evening increase in WT: WTOnset (WTOn) and "WT increase onset" (WTiO) was found to anticipate the evening increase in melatonin, while decreases in motor activity (Activity Offset or AcOff), body position (Position Offset (POff)), integrative TAP (a combination of WT, activity and body position) (TAPOffset or TAPOff) and an increase in declared sleep propensity were phase delayed with respect to DLMO. The phase markers obtained from subjective sleep (R = 0.811), WT (R = 0.756) and the composite variable TAP (R = 0.720) were highly and significantly correlated with DLMO. The findings strongly support a new method to calculate circadian phase based on WT (WTiO) that accurately predicts and shows a temporal association with DLMO. WTiO is especially recommended due to its simplicity and applicability to clinical use under conditions where knowing endogenous circadian phase is important, such as in cancer chronotherapy and light therapy.

Electroencephalography (EEG) recordings represent a vital component of the assessment of sleep physiology, but the methodology presently used is costly, intrusive to participants, and laborious in application. There is a recognized need to develop more easily applicable yet reliable EEG systems that allow unobtrusive long-term recording of sleep-wake EEG ideally away from the laboratory setting. cEEGrid is a recently developed flex-printed around-the-ear electrode array, which holds great potential for sleep-wake monitoring research. It is comfortable to wear, simple to apply, and minimally intrusive during sleep. Moreover, it can be combined with a smartphone-controlled miniaturized amplifier and is fully portable. Evaluation of cEEGrid as a motion-tolerant device is ongoing, but initial findings clearly indicate that it is very well suited for cognitive research. The present study aimed to explore the suitability of cEEGrid for sleep research, by testing whether cEEGrid data affords the signal quality and characteristics necessary for sleep stage scoring. In an accredited sleep laboratory, sleep data from cEEGrid and a standard PSG system were acquired simultaneously. Twenty participants were recorded for one extended nocturnal sleep opportunity. Fifteen data sets were scored manually. Sleep parameters relating to sleep maintenance and sleep architecture were then extracted and statistically assessed for signal quality and concordance. The findings suggest that the cEEGrid system is a viable and robust recording tool to capture sleep and wake EEG. Further research is needed to fully determine the suitability of cEEGrid for basic and applied research as well as sleep medicine.

Quantification of sleep is important for the diagnosis of sleep disorders and sleep research. However, the only widely accepted method to obtain sleep staging is by visual analysis of polysomnography (PSG), which is expensive and time consuming. Here, we investigate automated sleep scoring based on a low‐cost, mobile electroencephalogram (EEG) platform consisting of a lightweight EEG amplifier combined with flex‐printed cEEGrid electrodes placed around the ear, which can be implemented as a fully self‐applicable sleep system. However, cEEGrid signals have different amplitude characteristics to normal scalp PSG signals, which might be challenging for visual scoring. Therefore, this study evaluates the potential of automatic scoring of cEEGrid signals using a machine learning classifier (“random forests”) and compares its performance with manual scoring of standard PSG. In addition, the automatic scoring of cEEGrid signals is compared with manual annotation of the cEEGrid recording and with simultaneous actigraphy. Acceptable recordings were obtained in 15 healthy volunteers (aged 35 ± 14.3 years) during an extended nocturnal sleep opportunity, which induced disrupted sleep with a large inter‐individual variation in sleep parameters. The results demonstrate that machine‐learning‐based scoring of around‐the‐ear EEG outperforms actigraphy with respect to sleep onset and total sleep time assessments. The automated scoring outperforms human scoring of cEEGrid by standard criteria. The accuracy of machine‐learning‐based automated scoring of cEEGrid sleep recordings compared with manual scoring of standard PSG was satisfactory. The findings show that cEEGrid recordings combined with machine‐learning‐based scoring holds promise for large‐scale sleep studies.

Isolation from external time cues allows endogenous circadian rhythmicity to be demonstrated. In this study, also filmed as a television documentary, we assessed rhythmic changes in a healthy man time isolated in a bunker for 9 days/nights. During this period the lighting conditions were varied between: (1) self-selected light/dark cycle, (2) constant dim light, and (3) light/dark cycle with early wake up. A range of variables was assessed and related to the sleep-wake cycle, psychomotor and physical performance and clock-time estimation. This case study using modern non-invasive monitoring techniques emphasizes how different physiological circadian rhythms persist in temporal isolation under constant dim light conditions with different waveforms, free-running with a period (τ) between 24 and 25 h. In addition, a significant correlation between time estimation and mid-sleep time, a proxy for circadian phase, was demonstrated.

Melatonin is one of the most phylogenetically conserved signals in biology. Although its original function was probably related to its antioxidant capacity, this indoleamine has been “adopted” by multicellular organisms as the “darkness signal” when secreted in a circadian manner and is acutely suppressed by light at night by the pineal gland. However, melatonin is also produced by other tissues, which constitute its extrapineal sources. Apart from its undisputed chronobiotic function, melatonin exerts antioxidant, immunomodulatory, pro-apoptotic, antiproliferative, and anti-angiogenic effects, with all these properties making it a powerful antitumor agent. Indeed, this activity has been demonstrated to be mediated by interfering with various cancer hallmarks, and different epidemiological studies have also linked light at night (melatonin suppression) with a higher incidence of different types of cancer. In 2007, the World Health Organization classified night shift work as a probable carcinogen due to circadian disruption, where melatonin plays a central role. Our aim is to review, from a global perspective, the role of melatonin both from pineal and extrapineal origin, as well as their possible interplay, as an intrinsic factor in the incidence, development, and progression of cancer. Particular emphasis will be placed not only on those mechanisms related to melatonin’s antioxidant nature but also on the recently described novel roles of melatonin in microbiota and epigenetic regulation.